1. Field of the Invention
This invention relates to a system and method for detecting tremors such as derived from Parkinson's Disease and, more particularly, to such systems and methods which involve detecting movement and processing signals representative of movement so as to discriminate tremor-derived signals from activity and non-tremor signals.
2. Description of the Prior Art
Monitoring of patients to determine the occurrence of Parkinson's tremors is known in the art, although very few long-term tremor registrations have been reported in the literature. The literature has reported 24-hour recordings, but no easily applicable and useful tool has been provided. Prior known monitoring systems generally comprise some arrangement for taking an electromyogram or accelerometer signal and transmitting received signals and/or data to an on-line recorder. Data analysis normally takes place off-line, which is very time consuming. Other systems, so-called actometers, generally count movements of a patient's limb, e.g., arm or leg, but do not accurately discriminate between movements representative of tremors and those representative of other forms of movement or activity. Moreover, no index of the average acceleration of movements is given in such a system. See, for example, U.S. Pat. No. 4,353,375, which discloses the general concept of detecting arm or leg movement, but which does not suggest how to separate out tremor signal from other activity signals.
Our investigations have confirmed the shortcomings of the prior art. We have registered movements in ten Parkinsonian patients (both sexes, ages 43 to 89) and twenty healthy volunteers (both sexes, ages 26 to 67). Each patient wore an accelerometer on the wrist, the output of which was continuously recorded on a portable analog instrumentation recorder for 24 hours. Recordings were ambulant, and no restrictions on movements were made. Data were sampled with a frequency of 100 Hz for off-line computer analysis. The attempt to discriminate tremor from non-pathological movements by frequency was not satisfactory: fast Fourier transforms showed that the movement patterns overlapped in frequency range. Thus, there remains a need for a system and method which reliably discriminates reliable tremor signals from activity and non-tremor-induced signals. There further remains a need in the art for obtaining data by which tremor activity can be classified and analyzed so as to optimally indicate desired treatment, i.e., drug level setting by the physician automatic drug injection.